1. Field of the Invention
This invention relates to processing for forming a plurality of unsharp image signals, which have different frequency characteristics, from an image signal. This invention also relates to frequency emphasis processing for emphasizing high frequency components of the image signal by utilizing the unsharp image signals. This invention further relates to a dynamic range compressing process for rendering the level of contrast of the original image low by utilizing the unsharp image signals.
2. Description of the Prior Art
Techniques for obtaining an image signal, which represents an image, carrying out appropriate image processing on the image signal, and thereafter reproducing a visible image from the processed image signal have heretofore been carried out in various fields. For example, in methods for carrying out such techniques, an image is transformed into multi-resolution images by a Fourier transform, a wavelet transform, a sub-band transform, or the like, and the image signal representing the image is thereby decomposed into signals falling within a plurality of different frequency bands. Thereafter, of the decomposed signals, a signal falling within a desired frequency band is subjected to predetermined image processing.
As one of such methods, a method has been proposed, wherein an original image is transformed into multi-resolution images by utilizing an unsharp mask filter as in the technique using the wavelet transform, and image processing is then carried out on an unsharp image signal representing the unsharp image of each solution. The proposed method is utilized in image processing of radiation images, and the like.
Also, in the field of radiation image processing, when a radiation image (i.e., a tomographic image) of a tomographic plane is recorded with a tomographic image recording operation described in, for example, U.S. Pat. No. 4,581,535, it often occurs that the amount of transmitted radiation changes sharply at a portion, which is located at a position other than the tomographic plane. In such cases, an image pattern of such a portion occurs as an interfering pattern (or an interfering shadow) in the direction, along which the recording medium moves, and at a center region which is to be used in the radiation image. (Such an interfering pattern will hereinafter be referred to as the "flow pattern.") An image processing method for eliminating the flow pattern is proposed in, for example, Japanese Unexamined Patent Publication No. 3(1991)-276265. With the proposed image processing method, low frequency components corresponding to the flow pattern are removed from the image signal, which represents the radiation image obtained from the tomographic image recording operation, and an image free of the flow pattern is thereby obtained from the resulting image signal. The unsharp image signal described above can also be utilized in the process for eliminating the flow pattern.
The applicant proposed the methods for carrying out frequency emphasis processing on an image signal by utilizing an unsharp image signal in order that a visible radiation image having good image quality can be reproduced and used as an effective tool in, particularly, the accurate and efficient diagnosis of an illness. The methods for carrying out the frequency emphasis processing are disclosed in, for example, U.S. Pat. Nos. 4,315,318 and 4,317,179. With the frequency emphasis processing, an unsharp mask image signal (hereinbelow often referred to as the unsharp image signal) Sus is subtracted from an original image signal Sorg, which has been detected from a radiation image. The obtained difference value is multiplied by an emphasis coefficient .beta.. The resulting product is then added to the original image signal Sorg. In this manner, predetermined frequency components in the image can be emphasized. The frequency emphasis processing is represented by Formula (1) shown below. EQU Sproc=Sorg+.beta..times.(Sorg-Sus) (1)
wherein Sproc represents the signal obtained from the frequency emphasis processing, Sorg represents the original image signal, Sus represents the unsharp image signal, and .beta. represents the emphasis coefficient.
The unsharp image signal Sus can be obtained by carrying out an operation with Formula (2) EQU Sus=.EPSILON.Sorg/(M.times.N) (2)
on the image signal components of the original image signal Sorg, which represent M.times.N picture elements surrounding a middle picture element. By way of example, each of picture elements located at every second row and every second column in the array of picture elements constituting the image is taken as the middle picture element.
The unsharp image signal Sus representing an unsharp image, which results from the unsharp mask processing and has a resolution lower than the resolution of the original image, can also be obtained by utilizing an unsharp mask filter, which has a predetermined size, and calculating the mean value or the weighted mean value of the values of the picture elements located within the unsharp mask filter.
The applicant also proposed a method for compressing a dynamic range of an image, wherein an unsharp image signal is utilized, and the level of contrast of the parts of the image having a high or low image density or the level of contrast of the whole image is rendered low such that the difference between the highest image density and the lowest image density in the original image may become small, i.e. such that the dynamic range of the original image may become narrow. The method for compressing a dynamic range of an image is disclosed in, for example, U.S. Pat. No. 5,454,044. The proposed method comprises the steps of calculating an unsharp image signal Sus from the original image signal representing the original image, and processing the original image signal with Formula (3) EQU Sproc=Sorg+f(Sus) (3)
wherein f(Sus) represents a function, the value of which decreases monotonically as the value of the unsharp image signal Sus increases. In this manner, a processed image signal Sproc is obtained, which represents an image having a dynamic range narrower than the dynamic range of the original image. With the proposed method, both the dynamic range of parts of the image, which parts have low levels of image density, and the dynamic range of parts of the image, which have high levels of image density, can be compressed appropriately. Also, in cases where the differential coefficient of the function f(Sus) is set to be continuous, no artificial contour occurs in the image represented by the processed image signal Sproc. In this manner, the range of image density of the image can be compressed such that the parts of the image covering a wide range of image density can be used and may have good image quality in the reproduced visible image, and the image quality of fine image structures at each of parts having various levels of image density may be kept well.
In the image processing described above, in order for the original image to be transformed into the multi-resolution images by utilizing unsharp mask filters, it is necessary to use a plurality of filters having different sizes. In particular, in order for an unsharp image having a low resolution to be obtained, it is necessary to use a filter having a large size. However, if the size of the filter becomes large, the amount of operations for carrying out the filtering process will become very large, and a long time will be required to carry out the operations for conducting the unsharp mask processing. Also, it will become necessary to use a storage means having a large capacity for storing the information, which represents the plurality of the filters for obtaining the plurality of unsharp images having different levels of resolution. Therefore, the apparatus for carrying out the processing cannot be kept small, and the cost of the apparatus cannot be kept low.
Further, in cases where the unsharp image signal is formed with the unsharp mask filter, in the region in the vicinity of an edge in the image, at which the image density changes sharply, the unsharp image signal is affected by the image density of the edge in the image. Therefore, if the frequency emphasis processing, the dynamic range compressing process, or the flow pattern eliminating process described above is carried out by using the unsharp image signal, the problems will occur in that an artifact, such as overshoot, undershoot, or an artificial contour, occurs, and the image quality of the image obtained from the processing cannot be kept well.